18 results with keyword: 'fuzzy pid controller design dof industrial robot manipulator'
Figure 6 shows the design of 4 DOF arm robot manipulator assigned to pick and place green object.. Robot base height is 10 cm to ensure robot flexibility in picking and placing
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The inverse kinematic equation is to find the joint variables of the robot manipulator for a given position and orientation of the robot hand.. The computation of the inverse
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The response of all links of 3-DOF robotics manipulator under the PID controller is represented when the desired angles be: unit step, sinusoidal and unit step and
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Six degree of freedom missile (6-DOF); fractional PID controller (FPID); gain schedule fractional PID controller (GSFPID); Simulink design optimization; wind effect;
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PID controller is not sufficient to obtain the desired tracking control performance because of the nonlinearity of the robot manipulator, so nonlinear controller
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DEVELOPMENT OF A CASCADE PID FUZZY LOGIC CONTROLLER FOR WALL FOLLOWING MOBILE
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This paper investigates the design and implementation of a fuzzy logic PID controller, then application of this fuzzy logic PID controller in synchronous
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Sub- sequently, an equivalent adaptive fuzzy controller is proposed to design a robust control law for trajectory tracking of a two-link robot manipulator with reduced control
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Different control techniques have been applied to the flexible link manipulator systems in the literature [1-10], they include: Proportional Integral Derivative (PID)
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In this study hybrid LUS-TLBO based conventional PID controller & PID controller with derivative filter (PIDF) and fuzzy PID controller & fuzzy PID controller
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[21] Congying Qiu and Yibin Huang, ”The Design of Fuzzy Adaptive PID Controller of Two-Wheeled Self- Balancing Robot,” International Journal of Information and Electronics
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Robotic Industries Association defined an industrial robot system include the robot(s) (hardware and software) consisting of manipulator, power supply, controller,
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In this paper, design of controller for robot manipulator system using backstepping approach combined with Luenberger observer is presented for the robotic manipulator
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Control techniques such as linear control, optimal control, adaptive control, sliding-mode control, neural networks, or fuzzy logic deal with the control of
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ANFIS editor in Matlab is used to design the controller, Figure 3.5 shows the ANFIS editor’s window and the training data set that contains desired input/output data
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On the other side, we proved that the proposed controller is more efficient to control the robot manipulator to follow the desired trajectory compared to classical tuning
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RESULTS AND DISCUSSION 78 4.1 Comparison of a conventional PID, CTC and SMC 78 4.1.1 Comparison of the Tracking Data and Information 79 4.1.2 Comparison of the Actuation Torque τi
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The proposed Fuzzy C-Means controller applied to 2-link flexible robot manipulator has been tested for both step and ramp inputs and compared with normal CTC and reference
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